A non-informative prior is a type of prior distribution in Bayesian statistics that provides minimal or no information about the parameter being estimated. This approach allows the data to play a more significant role in shaping the posterior distribution, leading to a more objective analysis. Non-informative priors are particularly useful when there is little prior knowledge available, allowing for greater flexibility in modeling.
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